Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

What is Evolutionary History?02:35

What is Evolutionary History?

43.0K
Scientists record evolutionary history by analyzing fossil, morphological, and genetic data. The fossil record documents the history of life on Earth and provides evidence for evolution. However, both fossil and living organisms offer evidence that outlines Earth’s evolutionary history.
43.0K
Genetics of Speciation02:16

Genetics of Speciation

21.0K
Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
21.0K
Evolutionary Psychology01:20

Evolutionary Psychology

973
Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the...
973
What is Population Genetics?01:25

What is Population Genetics?

64.5K
A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
64.5K
Criticisms of the Evolutionary Perspective01:23

Criticisms of the Evolutionary Perspective

348
In a study where individuals posing as strangers offered compliments and proposed casual sex to students, the responses differed significantly based on gender. Not a single woman accepted the proposal, while 70% of the men agreed. This outcome provides a useful scenario to explore through the lens of evolutionary psychology and social learning theory, highlighting the diverse perspectives on human sexual behaviors.
Evolutionary psychology provides one explanation for these findings, suggesting...
348
Switching of BJT01:22

Switching of BJT

822
Switching behavior in Bipolar Junction Transistors (BJTs) is a fundamental aspect utilized in various electronic circuits, particularly for digital logic applications like switches and amplifiers. In a typical switching circuit, a BJT alternates between cut-off and saturation modes, corresponding to the "off" and "on" states, respectively, thus behaving like an ideal switch.
Cut-off Mode ("Off" State): In this state, both the emitter-base and collector-base junctions are...
822

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same author

Mirror Descent Safe Policy Optimization for Reinforcement Learning Agents.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Robust Multiobjective Evolutionary Algorithm Based on Surrogate-Assisted Robust Distance Metric.

IEEE transactions on cybernetics·2026
Same author

Guiding Multiagent Multitask Reinforcement Learning by a Hierarchical Framework With Logical Reward Shaping.

IEEE transactions on cybernetics·2025
Same author

Expensive Multiobjective Optimization Guided by Attention-Enhanced Generative Models.

IEEE transactions on neural networks and learning systems·2025
Same author

Multidomain Evolutionary Optimization on Combinatorial Problems in Complex Networks.

IEEE transactions on cybernetics·2025

Related Experiment Video

Updated: Jan 25, 2026

Measuring the Switch Cost of Smartphone Use While Walking
07:00

Measuring the Switch Cost of Smartphone Use While Walking

Published on: April 30, 2020

2.2K

Evolving connectivity between genetic oscillators and switches using evolutionary algorithms.

Spencer Angus Thomas1, Yaochu Jin

  • 1Department of Computing, University of Surrey, Guildford, Surrey GU2 7XH, UK.

Journal of Bioinformatics and Computational Biology
|June 26, 2013
PubMed
Summary

Artificial evolution successfully coupled simple gene regulatory motifs into complex networks. This demonstrates how modularisation and specialisation drive the evolution of gene regulatory networks.

More Related Videos

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER
07:26

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

12.7K
Quantitative Analysis by Thermogravimetry-Mass Spectrum Analysis for Reactions with Evolved Gases
06:51

Quantitative Analysis by Thermogravimetry-Mass Spectrum Analysis for Reactions with Evolved Gases

Published on: October 29, 2018

10.0K

Related Experiment Videos

Last Updated: Jan 25, 2026

Measuring the Switch Cost of Smartphone Use While Walking
07:00

Measuring the Switch Cost of Smartphone Use While Walking

Published on: April 30, 2020

2.2K
Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER
07:26

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

12.7K
Quantitative Analysis by Thermogravimetry-Mass Spectrum Analysis for Reactions with Evolved Gases
06:51

Quantitative Analysis by Thermogravimetry-Mass Spectrum Analysis for Reactions with Evolved Gases

Published on: October 29, 2018

10.0K

Area of Science:

  • Computational Biology
  • Systems Biology
  • Evolutionary Biology

Background:

  • Gene regulatory networks (GRNs) are crucial for cellular function.
  • The evolution of complex GRNs from simple regulatory motifs is hypothesised but poorly understood.
  • Key evolutionary processes include modularisation, gene duplication, and functional specialisation.

Purpose of the Study:

  • To computationally simulate the evolution of complex GRNs from simple motifs.
  • To investigate the mechanisms of modularisation, duplication, and specialisation in GRN evolution.
  • To explore the connectivity preferences and parameter thresholds in evolving GRNs.

Main Methods:

  • Utilised an evolutionary algorithm to simulate natural evolution in a computational environment.
  • Evolved the connection between a genetic oscillator and a toggle switch motif.
  • Analysed connectivity preferences based on coupling arrangements and objective set-ups.

Main Results:

  • Observed a connectivity preference between motifs, influenced by coupling arrangement, not objective set-up.
  • Identified a threshold in connection parameters critical for specific dynamics under certain coupling and objective conditions.
  • Demonstrated successful coupling of simple motifs into more complex, modular networks via artificial evolution.

Conclusions:

  • Simple regulatory motifs can be coupled through artificial evolution to form complex, modular GRNs.
  • Findings support the hypothesis that modularisation, duplication, and specialisation are key evolutionary mechanisms for GRNs.
  • This study provides a computational framework for understanding GRN evolution.